diff --git a/gtsam/nonlinear/NonlinearOptimizer-inl.h b/gtsam/nonlinear/NonlinearOptimizer-inl.h
index 33f8d7cd4..b1e1132f7 100644
--- a/gtsam/nonlinear/NonlinearOptimizer-inl.h
+++ b/gtsam/nonlinear/NonlinearOptimizer-inl.h
@@ -140,7 +140,7 @@ namespace gtsam {
 	// TODO: in theory we can't infinitely recurse, but maybe we should put a max.
 	/* ************************************************************************* */
 	template<class G, class C, class L, class S, class W>
-	NonlinearOptimizer<G, C, L, S, W> NonlinearOptimizer<G, C, L, S, W>::try_lambda(L& linear) {
+	NonlinearOptimizer<G, C, L, S, W> NonlinearOptimizer<G, C, L, S, W>::try_lambda(const L& linear) {
 
 		const Parameters::verbosityLevel verbosity = parameters_->verbosity_ ;
 		double lambda = parameters_->lambda_ ;
diff --git a/gtsam/nonlinear/NonlinearOptimizer.h b/gtsam/nonlinear/NonlinearOptimizer.h
index 3b088d8a6..17d7ec044 100644
--- a/gtsam/nonlinear/NonlinearOptimizer.h
+++ b/gtsam/nonlinear/NonlinearOptimizer.h
@@ -107,11 +107,6 @@ namespace gtsam {
 		// The dimensions of each linearized variable
 		const shared_dimensions dimensions_;
 
-		// Recursively try to do tempered Gauss-Newton steps until we succeed
-//		NonlinearOptimizer try_lambda(const L& linear,
-//				Parameters::verbosityLevel verbosity, double factor, Parameters::LambdaMode lambdaMode) const;
-		NonlinearOptimizer try_lambda(L& linear);
-
     /**
      * Constructor that does not do any computation
      */
@@ -250,6 +245,9 @@ namespace gtsam {
 		// suggested interface
 		NonlinearOptimizer gaussNewton() const;
 
+    /** Recursively try to do tempered Gauss-Newton steps until we succeed */
+    NonlinearOptimizer try_lambda(const L& linear);
+
 		/**
 		 * One iteration of Levenberg Marquardt
 		 */